System and method for processing insurance claims

ABSTRACT

Systems consistent with the present invention automatically process data associated with insurance claims to identify insurance claims with subrogation potential. Text from an insurance claim file may be automatically analyzed to extract data that can be quantified to determine whether the claim may have subrogation potential.

RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 60/451,000, filed Mar. 3, 2003, the disclosure of whichis incorporated herein by reference.

FIELD OF THE INVENTION

This invention relates to systems and methods for processing insuranceclaims and particularly to systems and methods for processing dataassociated with insurance claims using a computer.

BACKGROUND OF THE INVENTION

In a typical insurance claim, an insured submits a claim to an insurancecompany for costs associated with an injury or property damage, and theinsurance company pays the claim. Some of the paid claims may be theresult of third party fault. For example, a third party driver may havecaused an accident that injured the insured. In such a case, theinsurance company may be able to recover all or a portion of the amountpaid on the claim from the responsible party. As a result, the insuredmay be required to subrogate the right to sue the at-fault third partyin favor of the insurance company. Using the insured's subrogatedrights, the insurance company may attempt to recover amounts paid on theclaim from any third party responsible for the injury or damage. Forinstance, if an insured's car is destroyed in an auto accident caused bya third party, the insured's insurance company may pay the insured forthe value of the car, and separately seek to recover the amount paidfrom the third party or the third party's insurance company.

One challenge for the insurance company in attempting to recover moneypaid on claims is that not all claims are the result of third partyfault. For example, a single-car accident in which the driver/insuredfalls asleep and hits a tree is not likely to have an at-fault thirdparty from which to recover. The insurance company must thereforedetermine which claims may be due to a third party fault and thereforehave subrogation potential.

Currently, insurance companies rely on methods such as claim adjusterreferrals and scheduled audits to identify cases in which there is achance for subrogation and recovery. However, these traditional methodsare inadequate because they miss recovery opportunities. Adjusterreferrals use an insurance adjuster to manually review a paid claim tomake recommendations regarding subrogation. Such a method is inadequateto identify all recoverable claims because the determination ofrecoverability is subjective, requires experience and knowledge, and isgenerally a secondary job responsibility for the adjuster. The qualityand consistency of adjuster referrals varies, leading to missed recoveryopportunities in some cases, while in others valuable resources arespent pursuing unproductive claims.

Scheduled audits are also problematic. In a scheduled audit, largenumbers of files are selected either at random or using primitiveselection criteria such as a claim amount or claim type. For instance,an insurance company might select for review all claims in which acollision payment was made. The selected claim files are then sent to anauditing company for a “closed claim study,” in which the insurancecompany is typically charged on a per-file-reviewed basis. The auditingcompany typically uses specially trained auditors to manually reviewfiles to determine if there is a chance for recovery on any of theclaims. The process is expensive and time consuming, and its successdepends largely on the initial selection of claims to review and thediligence and discretion of the auditors.

Automation of the subrogation potential determination has been difficultbecause the information required to make the determination is not easilyidentifiable within a claim file. Subrogation recognition factors areoften buried or obscured in adjuster notes that are accumulated over thelife of the claim. Moreover, the content and form of a claim file canvary widely from company to company and adjuster to adjuster. Some filesmay be handwritten and kept on paper, while others may be keptelectronically. Recognition and extraction of subrogation informationfrom such files has traditionally been a task requiring extensive manuallabor and significant expense.

SUMMARY OF THE INVENTION

Systems consistent with the present invention overcome the deficienciesof known systems by processing data associated with insurance claims inan efficient and accurate manner to identify claims with subrogationpotential. In one embodiment, text from an insurance claim file may beautomatically analyzed to extract data that can be quantified todetermine whether the claim may have subrogation potential.

In an embodiment of the present invention, a method for processinginsurance claims comprises analyzing text associated with an insuranceclaim to extract data elements related to the insurance claim'ssubrogation potential and assigning a score to each of the dataelements. Whether the insurance claim has subrogation potential isdetermined based on the scores assigned to each of the data elements.

In another embodiment, an insurance claim is processed by receiving textcorresponding to the insurance claim, automatically separating the textinto groups of words, analyzing the groups of words to extract dataelements, and assigning a value to each of the data elements, the valuereflecting each data element's relevance to claim subrogation potential.The values assigned to the data elements are evaluated to determinewhether the insurance claim has subrogation potential.

In still another embodiment of the present invention, a system forprocessing insurance claims comprises a text analyzer that analyzes textassociated with an insurance claim and extracts data elements related tothe insurance claim's subrogation potential, a rules engine that assignsa score to each of the data elements and determines if the insuranceclaim has subrogation potential based on the scores assigned to each ofthe data elements, and a processor to run the text analyzer and therules engine

Further in accordance with an embodiment of the present invention, asystem for processing insurance claims comprises a text analyzer thatreceives text corresponding to the insurance claim, automaticallyseparates the text into groups of words, and analyzes the groups ofwords to extract data elements, a rules engine that assigns a value toeach of the data elements, the value reflecting each data element'srelevance to claim subrogation potential, and evaluates the valuesassigned to the data elements to determine whether the insurance claimhas subrogation potential, and a processor that runs the text analyzer.

Additional features and embodiments of the invention will be set forthin part in the description which follows, and in part will be obviousfrom the description, or may be learned by practice of the invention.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate embodiments of the invention andtogether with the description, serve to explain the principles of theinvention. In the figures:

FIG. 1 is a block diagram of a computer system for the practice of anembodiment of the present invention;

FIG. 2 is a block diagram of an embodiment of the present inventionshowing the relationship between various software components;

FIG. 3 is a block diagram of a text extractor according to an embodimentof the present invention;

FIG. 4 is a flow diagram showing the steps carried out by a textextractor according to an embodiment of the present invention;

FIG. 5 is an example of a data table according to an embodiment of thepresent invention;

FIG. 6 is an example of a data table according to another embodiment ofthe present invention; and

FIG. 7 is a flow diagram of a process performed by a rules engineaccording to an embodiment of the present invention.

DETAILED DESCRIPTION

Insurance companies currently rely on methods such as adjuster referralsand scheduled audits to identify insurance claims that are potentiallyrecoverable, e.g., claims that have subrogation potential. Currentmethods depend on manual recognition of potential recovery opportunityand are expensive and time consuming. These manual processes are proneto miss recovery opportunities or to waste resources on claims that haveno subrogation potential. Subrogation recognition factors are oftenobscured in adjuster notes accumulated over the life of a claim, makingelectronic identification difficult. Utilizing innovative textextraction technology, one embodiment of the present invention enablesinsurance companies to analyze insurance claim data and identifypotential recovery opportunities accurately and efficiently.

Systems consistent with an embodiment of the present inventiondeconstruct claim files, including adjuster notes, into data structures,such as data tables that may be used for data warehousing, data mining,analytics, etc. This data may be evaluated using scores based on, forexample, industry practice, historical data, or state law, toautomatically estimate a claim's subrogation probability.

Reference will now be made in detail to embodiments of the presentinvention, examples of which are illustrated in the accompanyingdrawings. Wherever possible, the same reference numbers will be usedthroughout the drawings to refer to the same or like parts.

FIG. 1 is a block diagram of a computer system 100 for the practice ofan embodiment of the present invention. The system may include acomputer, which includes a central processing unit (CPU) 102 connectedwith a memory 104, an input unit 106, and an output unit 108. Computersystem 100 may include, for example, a commercially availableprogrammable computer, such as a personal computer (PC), or a speciallydesigned computer.

Memory 104 may store software and databases used by computer system 100.Memory 104 may be, for example, random access memory, read only memory,removable memory such as a CD-ROM, etc. Input unit 106 may be, forexample, a keyboard, a communication device connected to anothercomputer or network, a device for reading disks, or an optical scannerin conjunction with known optical character recognition (OCR) componentsand/or a combination of these types of input devices. Output unit 108may be, for instance, a display, a communication device connected toanother computer or network, a storage device, a printer, or a devicefor writing disks and/or a combination of these types of output devices.The components of system 100 may be contained in a single computer ormay be distributed across multiple computers. For example, system 100may be implemented across any type of network, e.g., the Internet, aLAN, or a WAN.

FIG. 2 is a block diagram of an embodiment of the present inventionshowing the relationship between various software components that may bestored in memory 104. Memory 104 may include a text extractor 202 and arules engine 204. Text extractor 202 may be, for example, softwareconfigured to analyze unstructured text in an insurance claim file andtransform it into usable data stored in a data structure such as a datatable. Rules engine 204 may be, for example, software configured toprocess data from the data tables to determine whether a particularclaim has subrogation potential. The operation of text extractor 202 andrules engine 204 will now be explained in greater detail.

FIG. 3 is a block diagram of text extractor 202 in greater detailaccording to an embodiment of the present invention. Text extractor 202may include a word parser 302, a sentence splitter 304, a grammaticalparser 306, a specialized dictionary 308, and data tables 310.

Word parser 302 may be a tool for breaking text into individual words.For example, a string of letters preceded and followed by a space may beidentified as a word by word parser 302. Sentence splitter 304 may be atool for grouping words into sentences. For example, a string of wordsfollowed by a punctuation mark such as a period may be designated as asentence by sentence splitter 304. Word parser 302 and sentence splitter304 may be implemented using, for example, Powerindexing analysissoftware provided by Xanalys, Inc.

Grammatical parser 306 may be a tool to analyze words and sentences todetermine what data may be relevant to a claim's subrogation potential.For example, grammatical parser 306 may separate field headings fromdata contained in the fields.

Dictionary 308 may be used by word parser 302, sentence splitter 304,and/or grammatical parser 306, for example to identify common insuranceterms or phrases that typically relate to claims with high subrogationpotential.

The results of processing by word parser 302, sentence splitter 304,grammatical parser 306, and/or specialized dictionary 308 may be storedin data tables 310. One skilled in the art will appreciate that textextractor 202 may include fewer or more components than shown in FIG. 3and that the one or more of the components may be combined ordistributed over multiple computers.

FIG. 4 is a flow diagram showing the steps carried out by text extractor202 according to an embodiment of the present invention. Initially,unstructured text is received by text extractor 202 (step 402). Forexample, an electronic claim file may be imported or handwrittenadjuster notes may be scanned using an optical character reader. Wordparser 302 separates the text into individual words based on predefinedrules (step 404). For instance, a string of letters preceded by a spaceand followed by a space may be designated to be a word by word parser302. Alternatively, word parser 302 may match strings of characters towords stored in specialized dictionary 308 to identify words.

The text, now a series of words, may be subject to further grouping andanalysis by sentence splitter 304 (step 406). In one embodiment, thewords may be grouped into sentences or non-sentence textual groupings bysentence splitter 304 using sequences of letters, spaces, words, andpunctuation. For instance, sentence splitter 304 may check eachsuccessive word to determine if punctuation follows the word. Ifpunctuation does follow the word, sentence splitter 304 identifies thetype of punctuation to determine whether the punctuation isend-of-sentence punctuation. For instance, if a word is followed by aperiod, sentence splitter 304 may determine if the period designates theend of a sentence. This may be accomplished by comparing the wordfollowed by the period to terms stored in specialized dictionary 308.For example, if the word “Dr.” is being analyzed, sentence splitter 304may compare the letter preceding the period to abbreviations stored inspecialized dictionary 308 and determine that the period does notdesignate the end of a sentence. If the word is not found in the list ofabbreviations, sentence splitter 304 may determine that the period isthe end of a sentence. Other contextual clues surrounding the period mayalso be considered. For instance, if a period is followed by two spacesand the next word is capitalized, sentence splitter 304 may determinethat the period is the end of a sentence.

Non-sentence textual groupings may be, for example, data fields from aclaim form. Insurance claim files may contain forms with spaces or datafields in which particular information has been entered by an insured ora claim adjuster. For example, a claim form may have data fields forpercentage fault, the state in which the loss occurred, payment type,and coverage codes. Because such information may not be in traditionalsentence form, sentence splitter 304 may separate the information ineach data field and group the information with a heading of the datafield. For example, in a file having an entry field heading “percentfault” and an entry of “50%,” the terms “percent fault” and “50%” may begrouped together as a non-sentence textual grouping.

Once the textual input has been grouped (e.g., into sentences andnon-sentence text groupings), grammatical parser 306 may determine thetype of grouping (step 408) and analyze the grouping accordingly. If thegroup is a sentence (step 408, Yes), grammatical parser 306 may identifythe grammatical role of the words in the sentence (step 410). Forinstance, in one embodiment, grammatical parser 306 identifies andextracts the subject, verb, and object of each sentence by comparing thewords in each sentence to terms stored in specialized dictionary 308,such as commonly used insurance claim terms. In the context of autoinsurance, specialized dictionary 308 may contain commonly used termsfor the actors (subject or object) such as insd., insured, IV, insuredvehicle, OV, other vehicle, claimant, clmt., etc. Specialized dictionary308 may also include commonly used terms for the action (verb) such as,for example, “struck,” “hit,” “collided,” “crashed,” etc. The contextand order of the terms may also be used to determine which words in thesentence correspond to subject, verb, and object. For example, in themost common sentence structure, the subject is followed by the verb,which is then followed by the object. Next, the parsed words are enteredinto data tables 310 (step 412). For example, the subject, object, andverb combinations identified by grammatical parser 306 may be enteredinto a data table.

If the group is a non-sentence textual group (step 408, No), thengrammatical parser 306 may determine which part of the grouping is adata entry field heading (e.g., percentage fault) and which part is anentry (e.g., 50%) (step 414). This may be aided by reference tospecialized dictionary 308 containing commonly used insurance terms. Forexample, specialized dictionary 308 may contain commonly used data entryfield headings such as state of loss, percentage fault, payment type,coverage code, etc. If part of the non-sentence grouping is found inspecialized dictionary 308, that portion of the grouping may beidentified as the data entry field heading and the remainder of thegrouping may be identified as the entry. Once the parts of the groupingare identified, they are stored in data tables 310 (step 416).Consistent with an embodiment of the present invention, all or a part ofthe process shown in FIG. 4 may be repeated until all of the receivedtext is analyzed. For example, grammatical parser 306 may repeat steps408-416 until each grouping is processed.

FIG. 5 is an example of a data table according to an embodiment of thepresent invention. Data table 500 represents a table of sentencesseparated into subject, verb, and object. Each row may represent datafrom a sentence, and the columns may correspond to the subject, verb,and object of the sentence. The combination in data table 500 mayrepresent the sentence “O.V struck I.V.”, i.e., the other vehicle struckthe insured vehicle. Data table 500 may include any number of rows andcolumns consistent with the present invention. Furthermore, the data maybe stored in other formats or data structures, such as a tree.

FIG. 6 is an example of a data table according to another embodiment ofthe present invention. Data table 600 represents a table of non-sentencetextual groupings separated into data entry field headings and entries.The rows may correspond to a particular non-sentence grouping while thecolumns refer to the type of data. The data stored in data table 600 mayrepresent two facts “Loss state-New Jersey” and “Paymenttype-collision.” Data table 600 may include any number of rows andcolumns consistent with the present invention. Furthermore, the data maybe stored in other formats or data structures, such as a tree.

Once the claim data has been analyzed and stored in data tables by textextractor 202, rules engine 204 may use the claim data to determinewhether the claim has subrogation potential, i.e., whether there is aparty, other than the insured, that may be responsible for the damage orinjury leading to the claim. Rules engine 204 may include a set of rulescreated based on factors such as the jurisdiction in which the lossoccurred, fault percentage, payment type, coverage codes, informationabout how the loss occurred, etc. These rules may be based on, forexample, industry practice (e.g., claims that have a fault percentageless than 50% are typically recoverable), historical data (e.g., claimscosting over $10,000 usually have had at least some recovery potential),and state law (e.g., a particular state may have very difficultsubrogation laws, making recovery of claims arising there unlikely).

FIG. 7 is a flow diagram of a process performed by rules engine 204according to an embodiment of the present invention. Based on a storedrule, rules engine 204 extracts the required data elements from datatables 310 (step 702). In one example, rules engine 204 may consider thedata elements of the loss state, the percentage fault, the payment type,and the description of the loss to determine whether a claim hassubrogation potential. Each of these data elements is obtained from datatables 310 previously created by text extractor 202. For example, theloss state, the percentage fault, and the payment type may be extractedfrom one or more data tables of non-sentence groupings such as datatable 600. Rules engine 204 identifies the desired data elements bymatching data field headings in the data table and extracting thecorresponding entry. The rules engine may obtain information about thedescription of the loss from a data table containing sentencecombinations of subjects, verbs, and objects, such as data table 500.

Each data element is then assigned a score, e.g., based on its value orcontext (step 704). For example, rules engine 204 may follow a rule thatif a claim file contains data showing the percentage fault is 100%,indicating that the insured was completely at fault, the percentagefault data element would be given a negative score because this factorwould make recovery impossible. The scoring rules may be determined, forexample, using existing historical data from claims files that havealready been processed. The data from each of the historical claimsfiles may be analyzed to develop a relationship between data values andthe possibility of recovery.

Scoring rules may also be based on the actor or action involved. Forexample, if the insured is identified as the actor, there is unlikely tobe another responsible party from which to recover. For instance, if thetextual phrase, “the insured struck the other vehicle” is input,grammatical parser 306 will extract “insured” as the actor, “struck” asthe verb, and “other vehicle” as the object. Rules engine 204 mayimplement a rule that, when the actor is “insured,” that data elementreceives a negative score because it is likely that the insured is atfault and there is no other party from which to recover.

In one embodiment, if the data element “loss description” includes thedata “rear-ended” or “struck while parked,” a rule may score the dataelement higher than if the data is “struck at an intersection” or“parking lot accident.” In another embodiment, a rule may assign a scorebased on the number or types of claim payments made. For example, if the“number of vehicles” is two or more and a related personal injury claimhas been paid, the score may be low or 0. In another rule, if the“insured driver” is the same as the named insured, then few or 0 pointsmay be assigned to the “insured driver” data element. If the “insureddriver” is not the named insured, then a number of points, e.g., 10points, may be assigned. In still another rule, if a “police reportnumber” data element shows that a police report is available, the dataelement may be given more points than if no police report is available.Other rules and data elements may also be used consistent with thepresent invention.

After scoring has been assigned to each of the data elements, the scoresare analyzed to determine a potential for subrogation of the claim. Forexample, the scores may be summed together (step 706). The sum may becompared to a threshold value to determine the likelihood of subrogation(step 708). If the sum is greater than a threshold, the claim hassubrogation potential. If the sum is less than the threshold, the claimdoes not. Alternatively, higher scores may indicate increased chance ofrecovery and lower scores indicate decreased chance of recovery. In oneembodiment, the threshold may be zero.

By automating and streamlining the processing of data associated withinsurance claims, systems consistent with the present invention make itfeasible for an insurance company to quickly and accurately analyze aninsurance claim to determine its subrogation potential.

Other embodiments of the invention will be apparent to those skilled inthe art from consideration of the specification and practice of theinvention disclosed herein. For example, a text extractor and a rulesengine may be implemented in software and stored on a CD-ROM oravailable for download over a network. Alternatively, the text extractorand the rules engine may be provided separately or by different parties.

It is intended that the specification and examples be considered asexemplary only, with a true scope and spirit of the invention beingindicated by the following claims.

1. A computer-implemented method for processing insurance claims in acomputer system having a plurality of software components, the methodcomprising: providing a processor and a memory storing computer readablecode accessible by the processor for processing the insurance claims,the computer readable code comprising a text analyzer, a rules engine,and a score analyzer, and executing the computer readable code by theprocessor to perform: identifying, by the text analyzer using aspecialized insurance dictionary, insurance data elements in textassociated with an insurance claim; extracting, by the text analyzer,the insurance data elements related to the insurance claim's subrogationpotential, the text comprising at least one of the following: sentencetextual groups and non-sentence textual groups; storing, by the textanalyzer, the extracted insurance data elements in data tablescorresponding to the insurance claim; developing a subrogation potentialscore by the rules engine for each of the insurance data elements,wherein the developing further comprises: calculating the subrogationpotential score using a set of rules created from existing historicalclaim data, or assigning the subrogation potential score using the setof rules; and determining, by the score analyzer, if the insurance claimhas subrogation potential based on the subrogation potential scoresdeveloped for each of the insurance data elements.
 2. Thecomputer-implemented method of claim 1, wherein the identifying furthercomprises: separating the text into words; collecting the words intogroups; and parsing the groups into the insurance data elements.
 3. Thecomputer-implemented method of claim 2, wherein the groups arenon-sentence groupings.
 4. The computer-implemented method of claim 2,wherein the groups are sentences.
 5. A computer-implemented method forprocessing an insurance claim in a computer system having a plurality ofsoftware modules, the method comprising: providing a processor and amemory storing computer readable code accessible by the processor forprocessing the insurance claim, the computer readable code comprising areceiving module, a separating module, a text analyzer, an assigningmodule, and an evaluating module, and executing the computer readablecode by the processor to perform: receiving text corresponding to theinsurance claim by the receiving module, the text comprising at leastone of the following: sentence textual groups and non-sentence textualgroups; automatically separating the text into groups of words by theseparating module; identifying, by the text analyzer using a specializedinsurance dictionary, insurance data elements of the insurance claim inthe groups of words; extracting, by the text analyzer, the insurancedata elements related to the insurance claim's subrogation potential;storing, by the text analyzer, the extracted insurance data elements indata tables corresponding to the insurance claim; developing a value foreach of the insurance data elements by the assigning module, the valuereflecting each insurance data element's relevance to the claimsubrogation potential, wherein the developing further comprises:calculating the value using a set of rules created from existinghistorical claim data, or assigning the value using the set of rules;and evaluating the values developed for the insurance data elements bythe evaluating module to determine whether the insurance claim hassubrogation potential.
 6. The computer-implemented method of claim 5,wherein the value is a subrogation potential score.
 7. Thecomputer-implemented method of claim 5, wherein the values are based onhistorical data about subrogation of insurance claims.
 8. Thecomputer-implemented method of claim 5, wherein the values are based onindustry practice regarding subrogation of insurance claims.
 9. Thecomputer-implemented method of claim 5, wherein the values are based onstate law regarding subrogation of insurance claims.
 10. A computersystem for processing insurance claims comprising: a processor; and amemory storing computer readable code accessible by the processor forprocessing the insurance claims, the computer readable code comprising:a text analyzer software component configured for: identifying insurancedata elements in text associated with an insurance claim using aspecialized insurance dictionary, extracting the insurance data elementsrelated to the insurance claim's subrogation potential, the textcomprising at least one of the following: sentence textual groups andnon-sentence textual groups, and storing, by the text analyzer softwarecomponent, the extracted insurance data elements in data tablescorresponding to the insurance claim; and a rules engine softwarecomponent configured for: developing a subrogation potential score foreach of the insurance data elements, wherein the developing furthercomprises: calculating the subrogation potential score using a set ofrules created from existing historical claim data, or assigning thesubrogation potential score using the set of rules; and determining ifthe insurance claim has subrogation potential based on the subrogationpotential scores developed for each of the insurance data elements. 11.The computer system of claim 10, wherein the text analyzer softwarecomponent further comprises: a word parser for separating the text intowords; a sentence splitter for collecting the words into groups; and agrammatical parser for parsing the groups into the insurance dataelements.
 12. The computer system of claim 11, wherein the specializedinsurance dictionary is used by at least one of the word parser, thesentence splitter, and the grammatical parser.
 13. A computer system forprocessing an insurance claim, comprising: a processor; a memory storingcomputer readable code accessible by the processor for processing theinsurance claims, the computer readable code comprising: a text analyzersoftware component configured for: receiving text corresponding to theinsurance claim, identifying insurance data elements in the text using aspecialized insurance dictionary, extracting the insurance dataelements, the text comprising at least one of the following: sentencetextual groups and non-sentence textual groups, and storing, by the textanalyzer software component, the extracted insurance data elements indata tables corresponding to the insurance claim; and a rules enginesoftware component configured for: developing a value for each of thedata elements, the value reflecting each insurance data element'srelevance to claim subrogation potential, wherein the developing furthercomprises: calculating the value using a set of rules created fromexisting historical claim data, or assigning the value using the set ofrules; and evaluating the values developed for the insurance dataelements to determine whether the insurance claim has subrogationpotential.
 14. The computer system of claim 13, further comprising aprocessor that runs the rules engine software component.
 15. Thecomputer system of claim 13, wherein the values are based on historicaldata about subrogation of insurance claims.
 16. The computer system ofclaim 13, wherein the values are based on industry practice regardingsubrogation of insurance claims.
 17. The computer system of claim 13,wherein the values are based on state law regarding subrogation ofinsurance claims.
 18. A computer usable medium having computer readablecode embodied therein for processing insurance claims, the computerreadable code comprising: an analyzing module for: identifying insurancedata elements in text associated with an insurance claim using aspecialized insurance dictionary, extracting the insurance data elementsrelated to the insurance claim's subrogation potential, the textcomprising at least one of the following: sentence textual groups andnon-sentence textual groups, and storing the extracted insurance dataelements in data tables corresponding to the insurance claim; anassigning module for developing a subrogation potential score for eachof the insurance data elements, wherein the developing furthercomprises: calculating the subrogation potential score using a set ofrules created from existing historical claim data, or assigning thesubrogation potential score using the set of rules; and a determiningmodule for determining if the insurance claim has subrogation potentialbased on the subrogation potential scores developed for each of theinsurance data elements.
 19. The computer usable medium of claim 18,wherein the analyzing module further comprises: a separating module forseparating the text into words; a collecting module for collecting thewords into groups; and a parsing module for parsing the groups into theinsurance data elements.
 20. A computer usable medium having computerreadable code embodied therein for processing an insurance claim, thecomputer readable code comprising: a receiving module for receiving textcorresponding to the insurance claim, the text comprising at least oneof the following: sentence textual groups and non-sentence textualgroups; a separating module for automatically separating the text intogroups of words; an analyzing module for: identifying insurance dataelements of an insurance claim the groups of words using a specializedinsurance dictionary, extracting the insurance data elements related tothe insurance claim's subrogation potential, and storing the extractedinsurance data elements in data tables corresponding to the insuranceclaim; an assigning module for developing a value for each of theinsurance data elements, the value reflecting each insurance dataelement's relevance to claim subrogation potential, wherein thedeveloping further comprises: calculating the value using a set of rulescreated from existing historical claim data, or assigning the valueusing the set of rules; and an evaluating module for evaluating thevalues developed for the insurance data elements to determine whetherthe insurance claim has subrogation potential.
 21. The computer usablemedium of claim 20, wherein the value is a subrogation potential score.22. A computer-implemented method for processing insurance claims in acomputer system having a plurality of software components, the methodcomprising: providing a processor and a memory storing computer readablecode accessible by the processor for processing the insurance claims,the computer readable code comprising a text analyzer and a referralengine, and executing the computer readable code by the processor toperform: identifying, by the text analyzer using a specialized insurancedictionary, insurance data elements in text associated with an insuranceclaim; extracting, by the text analyzer, the insurance data elementsrelated to the insurance claim's subrogation potential, the textcomprising at least one of the following: sentence textual groups andnon-sentence textual groups; storing, by the text analyzer, theextracted insurance data elements in data tables corresponding to theinsurance claim; and determining, as a function of subrogation potentialscores associated with at least a set of the insurance data elements bythe referral engine, wherein the subrogation potential scores aredeveloped by calculating the subrogation potential score using a set ofrules created from existing historical claim data, or assigning thesubrogation potential score using the set of rules, whether theinsurance claim is to be referred for subrogation.
 23. Thecomputer-implemented method of claim 22, further comprising: developingthe subrogation potential scores for the set of insurance data elements.24. The computer-implemented method of claim 22, wherein the identifyingfurther comprises: separating the text into words; collecting the wordsinto groups; and parsing the groups into the insurance data elements.25. The computer-implemented method of claim 22, further comprising:applying a rule that specifies the set of insurance data elements andthe subrogation potential scores associated with the set of insurancedata elements.
 26. A computer system for processing insurance claimscomprising: a processor; a memory storing computer readable codeaccessible by the processor for processing the insurance claims, thecomputer readable code comprising: a text analyzer software componentconfigured for: identifying insurance data elements in text associatedwith an insurance claim using a specialized insurance dictionary,extracting the insurance data elements related to the insurance claim'ssubrogation potential, the text comprising at least one of thefollowing: sentence textual groups and non-sentence textual groups, andstoring, by the text analyzer software component, the extractedinsurance data elements in data tables corresponding to the insuranceclaim; and a referral engine software component configured fordetermining, as a function of subrogation potential scores associatedwith at least a set of the insurance data elements, wherein thesubrogation potential scores are developed by calculating thesubrogation potential score using a set of rules created from existinghistorical claim data, or assigning the subrogation potential scoreusing the set of rules, whether the insurance claim is to be referredfor subrogation.
 27. The computer system of claim 26, wherein thereferral engine further develops the subrogation potential scores forthe set of insurance data elements.
 28. The computer system of claim 26,wherein the text analyzer software component further separates the textinto words, collects the words into groups, and parses the groups intothe insurance data elements.
 29. A computer usable medium havingcomputer readable code embodied therein for processing insurance claims,the computer readable code comprising: an analyzing module for:identifying insurance data elements in text associated with an insuranceclaim using a specialized insurance dictionary, extracting the insurancedata elements related to the insurance claim's subrogation potential,the text comprising at least one of the following: sentence textualgroups and non-sentence textual groups, and storing the extractedinsurance data elements in data tables corresponding to the insuranceclaim; a determining module for determining, as a function ofsubrogation potential scores associated with at least a set of theinsurance data elements, wherein the subrogation potential scores aredeveloped by calculating the subrogation potential score using a set ofrules created from existing historical claim data, or assigning thesubrogation potential score using the set of rules, whether theinsurance claim is to be referred for subrogation; and a processingmodule to run the analyzing module and the determining module.
 30. Thecomputer usable medium of claim 29, further comprising: an assigningmodule for developing the subrogation potential scores for the set ofinsurance data elements.
 31. The computer usable medium of claim 29,wherein the analyzing module further comprises: a separating module forseparating the text into words; a collecting module for collecting thewords into groups; and a parsing module for parsing the groups into theinsurance data elements.
 32. The computer usable medium of claim 29,further comprising: an applying module for applying a rule thatspecifies the set of insurance data elements and the subrogationpotential scores associated with the set of insurance data elements.